Compute Comparison

Scaleway

Specialist Cloud

Scaleway is a French GPU cloud offering H100 and A100 instances with strong GDPR compliance and EU data sovereignty, backed by managed Kubernetes and a full developer-friendly cloud platform. On-demand and reserved billing options are available across EU data centers, making it one of the most complete European GPU cloud options for teams that need both AI compute and broader cloud services. A natural fit for EU-based AI teams that want competitive European GPU pricing without vendor lock-in.

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Cheapest On-Demand

$5.14/hr

Cheapest Spot

GPU Listings

3

Billing

On-demand, Reserved

Performance Benchmarks

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Provider Info

Headquarters

Paris, France

Founded

2015

Regions

EU-West, EU-Central

Min Commitment

None

Support

Basic → Enterprise

Strengths

  • EU sovereignty
  • GDPR compliant
  • Competitive EU pricing
  • Managed Kubernetes

Limitations

  • Limited GPU catalog vs hyperscalers
  • Primarily European regions only
  • Less mature ML ecosystem vs AWS/GCP

Best For

EU-based AI teamsGDPR-sensitive workloadsFull-stack cloud users

Full GPU Catalog

GPU ModelvRAMOn-DemandSpotAvailabilityRegion
L40S48 GB$5.14MedEU-West
A100 80GB80 GB$10.23MedEU-West
H100 80GB80 GB$23.61MedEU-West

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Scaleway GPU pricing overview

Scaleway is a specialist GPU cloud provider headquartered in Paris, France. Scaleway is a French GPU cloud offering H100 and A100 instances with strong GDPR compliance and EU data sovereignty, backed by managed Kubernetes and a full developer-friendly cloud platform. On-demand and reserved billing options are available across EU data centers, making it one of the most complete European GPU cloud options for teams that need both AI compute and broader cloud services. A natural fit for EU-based AI teams that want competitive European GPU pricing without vendor lock-in. Billing is On-demand, Reserved with a minimum commitment of None. Available regions include EU-West, EU-Central. On-demand GPU instances can be provisioned in minutes with no upfront cost, making Scaleway suitable for both short-duration experiments and sustained production workloads.

Scaleway vs other GPU providers

Scaleway competes with providers including Lambda Labs, CoreWeave, RunPod, Paperspace, Vast.ai, and the major hyperscalers (AWS, Google Cloud, Azure) for GPU compute workloads spanning LLM training, fine-tuning, and inference serving. Key differentiators include: EU sovereignty; GDPR compliant; Competitive EU pricing. Use the side-by-side comparison tool above to see Scaleway pricing against any other provider across shared GPU models. For a broader market view, the live GPU prices table shows all 3 Scaleway listings alongside 94+ providers in a single sortable view.

Best use cases for Scaleway

Scaleway is best suited for: EU-based AI teams, GDPR-sensitive workloads, Full-stack cloud users. Support tiers range from Basic → Enterprise, making it viable for both individual researchers and enterprise teams with SLA requirements. There are currently 3 active GPU listings on Scaleway, covering H100 80GB, A100 80GB, L40S. For workloads requiring the highest single-GPU throughput, H100 SXM5 instances with NVLink interconnect deliver the best performance per dollar at scale. For cost-sensitive fine-tuning or inference of models up to 13B parameters, A100 40GB or RTX 4090 instances typically offer the best value.

Scaleway billing model and cost structure

Scaleway uses On-demand, Reserved pricing. On-demand instances are billed per second or per hour depending on the instance type, with no termination fees. Spot pricing is not currently available on this provider — all instances are on-demand. Reserved instance pricing, where available, can reduce costs by 30–60% for predictable long-running workloads. Always compare the effective hourly rate including egress, storage, and networking costs when evaluating total cost of ownership across providers.

Choosing the right GPU on Scaleway

GPU selection depends on model size, precision, and whether your workload is compute-bound or memory-bandwidth-bound. For LLM training above 30B parameters, H100 80GB SXM5 instances with NVLink are the standard choice — the 3,350 GB/s HBM3 bandwidth and 989 TFLOPS FP16 throughput make them 2–2.5× faster than A100 for transformer workloads. For inference of 7B–13B models in FP16 or BF16, A100 40GB offers the best cost-per-token on most providers. RTX 4090 instances are ideal for fine-tuning, prototyping, and quantized inference (INT4/INT8) of models up to 70B. Read the H100 vs A100 guide or the GPU benchmarks for ML guide for a full breakdown.

How Scaleway pricing data is collected

Prices shown are sourced from Scaleway's public pricing API or pricing page and refreshed every 15 minutes. On-demand rates reflect the current list price for a single GPU instance in the cheapest available region. Spot prices, where available, reflect interruptible instance rates at the time of the last snapshot. All prices are in USD per hour. Daily snapshots are retained for 90 days and visualised in the GPU price history charts — useful for identifying seasonal pricing patterns and evaluating whether current rates are above or below the 30-day average.

Evaluating managed LLM inference APIs as an alternative to self-hosted GPU compute? Compare live LLM token prices across OpenAI, Anthropic, Google, Groq, and 14+ other providers. The cheapest GPU cloud guide covers the break-even analysis between self-hosted and managed inference at different request volumes.

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On-demand from $5.14/hr — 3 GPU configurations available. On-demand, Reserved billing.

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